Du D - Search Results

1

Imbalanced Data Correction Based PET/CT Radiomics Model for Predicting Lymph Node Metastasis in Clinical Stage T1 Lung Adenocarcinoma.

Lv J, Chen X, Liu X, Du D, Lv W, Lu L, Wu H. Lv J, et al. Among authors: du d. Front Oncol. 2022 Jan 28;12:788968. doi: 10.3389/fonc.2022.788968. eCollection 2022. Front Oncol. 2022. PMID: 35155231 Free PMC article.

2

[Palm vein recognition based on end-to-end convolutional neural network].

Du D, Lu L, Fu R, Yuan L, Chen W, Liu Y. Du D, et al. Nan Fang Yi Ke Da Xue Xue Bao. 2019 Feb 28;39(2):207-214. doi: 10.12122/j.issn.1673-4254.2019.02.13. Nan Fang Yi Ke Da Xue Xue Bao. 2019. PMID: 30890510 Free PMC article. Chinese.

3

Machine Learning Methods for Optimal Radiomics-Based Differentiation Between Recurrence and Inflammation: Application to Nasopharyngeal Carcinoma Post-therapy PET/CT Images.

Du D, Feng H, Lv W, Ashrafinia S, Yuan Q, Wang Q, Yang W, Feng Q, Chen W, Rahmim A, Lu L. Du D, et al. Mol Imaging Biol. 2020 Jun;22(3):730-738. doi: 10.1007/s11307-019-01411-9. Mol Imaging Biol. 2020. PMID: 31338709

4

Subregional Radiomics Analysis of PET/CT Imaging with Intratumor Partitioning: Application to Prognosis for Nasopharyngeal Carcinoma.

Xu H, Lv W, Feng H, Du D, Yuan Q, Wang Q, Dai Z, Yang W, Feng Q, Ma J, Lu L. Xu H, et al. Among authors: du d. Mol Imaging Biol. 2020 Oct;22(5):1414-1426. doi: 10.1007/s11307-019-01439-x. Mol Imaging Biol. 2020. PMID: 31659574

5

Evaluation of the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with obstructive coronary artery disease.

Wang F, Xu W, Lv W, Du D, Feng H, Zhang X, Wang S, Chen W, Lu L. Wang F, et al. Among authors: du d. J Nucl Cardiol. 2021 Dec;28(6):3070-3080. doi: 10.1007/s12350-020-02160-x. Epub 2020 May 21. J Nucl Cardiol. 2021. PMID: 32440989

6

Integration of PET/CT Radiomics and Semantic Features for Differentiation between Active Pulmonary Tuberculosis and Lung Cancer.

Du D, Gu J, Chen X, Lv W, Feng Q, Rahmim A, Wu H, Lu L. Du D, et al. Mol Imaging Biol. 2021 Apr;23(2):287-298. doi: 10.1007/s11307-020-01550-4. Epub 2020 Oct 8. Mol Imaging Biol. 2021. PMID: 33030709

7

Reply to Letter to Editor RE: "Integration of PET/CT Radiomics and Semantic Features for Differentiation Between Active Pulmonary Tuberculosis and Lung Cancer".

Du D, Gu J, Chen X, Lv W, Feng Q, Rahmim A, Wu H, Lu L. Du D, et al. Mol Imaging Biol. 2021 Dec;23(6):975-977. doi: 10.1007/s11307-021-01634-9. Epub 2021 Jul 26. Mol Imaging Biol. 2021. PMID: 34312805 No abstract available.

8

Identification of Stage IIIC/IV EGFR-Mutated Non-Small Cell Lung Cancer Populations Sensitive to Targeted Therapy Based on a PET/CT Radiomics Risk Model.

Shao D, Du D, Liu H, Lv J, Cheng Y, Zhang H, Lv W, Wang S, Lu L. Shao D, et al. Among authors: du d. Front Oncol. 2021 Nov 2;11:721318. doi: 10.3389/fonc.2021.721318. eCollection 2021. Front Oncol. 2021. PMID: 34796106 Free PMC article.

9

Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.

Du D, Lv W, Lv J, Chen X, Wu H, Rahmim A, Lu L. Du D, et al. Eur Radiol. 2023 Apr;33(4):2426-2438. doi: 10.1007/s00330-022-09229-w. Epub 2022 Nov 10. Eur Radiol. 2023. PMID: 36355196

10

Deep learning PET/CT-based radiomics integrates clinical data: A feasibility study to distinguish between tuberculosis nodules and lung cancer.

Zhang X, Dong X, Saripan MIB, Du D, Wu Y, Wang Z, Cao Z, Wen D, Liu Y, Marhaban MH. Zhang X, et al. Among authors: du d. Thorac Cancer. 2023 Jul;14(19):1802-1811. doi: 10.1111/1759-7714.14924. Epub 2023 May 14. Thorac Cancer. 2023. PMID: 37183577 Free PMC article.

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